As per [85], a decision-aid tool combining QFD, fuzzy linear regression and MOP is used to select the best 3PL for Turkish auto part manufacturers. Five main criteria are considered, namely: cost, timeless, service quality, flexibility, and reputation.
Recently, Hsu and Liou [86] developed an integrated model that combined DEMATEL and ANP by considering the same criteria as those used in [80]. The model is applied to the Taiwanese airline case.
5. Conclusions, limitations and future research
In this paper, 67 articles on 3PL selection are analyzed in deep to identify the criteria and methods most used in this selection.
In terms of criteria, this review shows that the 3PL selection process is based on a large number of attributes; this reflects the richness of the bundle of services that a 3PL offers as well as the usual difficulties of precisely defining the nature of quality dimensions in a service environment. For example, Spencer et al. [17] listed 23 potential factors, Leahy et al. [38] used 25, and Govindan et al. [57] identified 35 in their studies. In broad terms, our analysis allows to organize the 3PL selection criteria in 11 main groups, as listed in Table 3.
According to the Pareto method, Table 3 lists that the most commonly used criteria are: cost, relationship, services, quality, information/equipment system, flexibility, and delivery. These criteria represent 79.59%, while professionalism, financial position, location, and reputation represent the remaining 20.41%. Each criterion is described and defined by a set of attributes.
There are 46 articles (68.66%) considering “cost” in the 3PL selection process. This criterion is related to attributes including price, cost reduction, low cost distribution, expected leasing cost, operation cost, warehousing cost, and cost savings.
The 2nd most used criterion is “relationship” with 44 papers (65.67%) and its related attributes include sustainable relationship, long-term cooperation, alliance, compatibility, comparable culture, similar values and goals, dependence, attachment, reciprocity, willingness and attitude, trust, and integration level index.
The 3rd most used criterion is “services” with 42 papers (62.69%) and it is defined by a group of attributes such as breadth or range of service, characterization/specialization of services, variety of available services, pre-sale/post-sale customer services, and value-added services.
The criterion “quality” is also important and comes at 4th position, with 40 papers (59.70%) and it is related to attributes such as service quality, continuous improvement, SQAS/ISO standards, customer satisfaction, and risk management.
In terms of methods, Table 4 summarizes most of those discussed in this paper while Table 5 gives some strengths and weaknesses of these methods.
According to Table 4 results, MCDM are widely cited with 38 papers and the most of them (81.58%) are integrated with methods in this same category or with other techniques such as ANN, MIP, and DEA. Statistical methods arrive at 2nd position with 28 papers, followed by mathematical programming with 15 papers, and artificial intelligence with 8 papers.
Individually, the correlation method is widely applied with 24 papers (26.97%).This is due to the fact that the majority of studies on 3PL selection is of empirical type. FST comes at 2nd position with 10 papers (11.24%) and is used to model uncertainty and inaccuracy of the criteria weights. AHP is also cited with 8 papers (8.99%) due to its simplicity, its easiness of use, and its great flexibility. The methods such as ELECTRE, utility theory, logit regression, DP, TCO, and others artificial intelligence techniques are rarely used.
Although the above mentioned approaches can deal with multiple and conflicting criteria, they have not taken into consideration the impact of business objectives and requirements of company stakeholders on the evaluating criteria. In reality, the weightings of criteria depend a lot on business priorities and strategies. In cases where the weightings are assigned subjectively without considering the “voice” of company stakeholders, the 3PL selected may not provide what the company exactly wants.
Thus, an overall suggestion for future research in the 3PL selection field will take into account the following elements:
– The consideration of the “voice” of company stakeholders in the determination of the criteria weightings. In this sense, it could be more useful to integrate quality tools such as QFD. This method is only mentioned in two recent publications [84, 85].
– The exploration of others methods such as ABC [87], PROMETHEE, SMART and others artificial intelligence techniques [48], widely used in the case of supplier selection of goods.
– The majority (82.09%) studies are empirical in nature and are generally related to a geographical region or country. The few comparative studies between countries or regions that have been conducted are those of Fawcett and Smith [21], and Millen et al. [24]. It would be interesting to do further studies in this direction, especially in the current context of markets’ globalization and increased international logistics.
– The 3PL selection studies are weakly theoretical with only 17.91% of the articles. A more comprehensive conceptual framework is needed, and must consider all qualitative, quantitative, tangibles, intangibles, strategic, and operational criteria.
– This review can also be extended to the analysis of doctoral thesis, conference articles and other databases.
– Finally, this paper may help researchers for understanding the inadequacy in the 3PL selection literature and finding the gaps for work to be done in future.
As per [85], a decision-aid tool combining QFD, fuzzy linear regression and MOP is used to select the best 3PL for Turkish auto part manufacturers. Five main criteria are considered, namely: cost, timeless, service quality, flexibility, and reputation.
Recently, Hsu and Liou [86] developed an integrated model that combined DEMATEL and ANP by considering the same criteria as those used in [80]. The model is applied to the Taiwanese airline case.
5. Conclusions, limitations and future research
In this paper, 67 articles on 3PL selection are analyzed in deep to identify the criteria and methods most used in this selection.
In terms of criteria, this review shows that the 3PL selection process is based on a large number of attributes; this reflects the richness of the bundle of services that a 3PL offers as well as the usual difficulties of precisely defining the nature of quality dimensions in a service environment. For example, Spencer et al. [17] listed 23 potential factors, Leahy et al. [38] used 25, and Govindan et al. [57] identified 35 in their studies. In broad terms, our analysis allows to organize the 3PL selection criteria in 11 main groups, as listed in Table 3.
According to the Pareto method, Table 3 lists that the most commonly used criteria are: cost, relationship, services, quality, information/equipment system, flexibility, and delivery. These criteria represent 79.59%, while professionalism, financial position, location, and reputation represent the remaining 20.41%. Each criterion is described and defined by a set of attributes.
There are 46 articles (68.66%) considering “cost” in the 3PL selection process. This criterion is related to attributes including price, cost reduction, low cost distribution, expected leasing cost, operation cost, warehousing cost, and cost savings.
The 2nd most used criterion is “relationship” with 44 papers (65.67%) and its related attributes include sustainable relationship, long-term cooperation, alliance, compatibility, comparable culture, similar values and goals, dependence, attachment, reciprocity, willingness and attitude, trust, and integration level index.
The 3rd most used criterion is “services” with 42 papers (62.69%) and it is defined by a group of attributes such as breadth or range of service, characterization/specialization of services, variety of available services, pre-sale/post-sale customer services, and value-added services.
The criterion “quality” is also important and comes at 4th position, with 40 papers (59.70%) and it is related to attributes such as service quality, continuous improvement, SQAS/ISO standards, customer satisfaction, and risk management.
In terms of methods, Table 4 summarizes most of those discussed in this paper while Table 5 gives some strengths and weaknesses of these methods.
According to Table 4 results, MCDM are widely cited with 38 papers and the most of them (81.58%) are integrated with methods in this same category or with other techniques such as ANN, MIP, and DEA. Statistical methods arrive at 2nd position with 28 papers, followed by mathematical programming with 15 papers, and artificial intelligence with 8 papers.
Individually, the correlation method is widely applied with 24 papers (26.97%).This is due to the fact that the majority of studies on 3PL selection is of empirical type. FST comes at 2nd position with 10 papers (11.24%) and is used to model uncertainty and inaccuracy of the criteria weights. AHP is also cited with 8 papers (8.99%) due to its simplicity, its easiness of use, and its great flexibility. The methods such as ELECTRE, utility theory, logit regression, DP, TCO, and others artificial intelligence techniques are rarely used.
Although the above mentioned approaches can deal with multiple and conflicting criteria, they have not taken into consideration the impact of business objectives and requirements of company stakeholders on the evaluating criteria. In reality, the weightings of criteria depend a lot on business priorities and strategies. In cases where the weightings are assigned subjectively without considering the “voice” of company stakeholders, the 3PL selected may not provide what the company exactly wants.
Thus, an overall suggestion for future research in the 3PL selection field will take into account the following elements:
– The consideration of the “voice” of company stakeholders in the determination of the criteria weightings. In this sense, it could be more useful to integrate quality tools such as QFD. This method is only mentioned in two recent publications [84, 85].
– The exploration of others methods such as ABC [87], PROMETHEE, SMART and others artificial intelligence techniques [48], widely used in the case of supplier selection of goods.
– The majority (82.09%) studies are empirical in nature and are generally related to a geographical region or country. The few comparative studies between countries or regions that have been conducted are those of Fawcett and Smith [21], and Millen et al. [24]. It would be interesting to do further studies in this direction, especially in the current context of markets’ globalization and increased international logistics.
– The 3PL selection studies are weakly theoretical with only 17.91% of the articles. A more comprehensive conceptual framework is needed, and must consider all qualitative, quantitative, tangibles, intangibles, strategic, and operational criteria.
– This review can also be extended to the analysis of doctoral thesis, conference articles and other databases.
– Finally, this paper may help researchers for understanding the inadequacy in the 3PL selection literature and finding the gaps for work to be done in future.
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